JP2003134339A - Image forming apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To reduce moire generated in the gray level transformation of an input image including periodicities, to reduce the generations of isolated dots, and to increase the speed of a picture-tone converting processing. SOLUTION: In an image forming apparatus 100 for converting image data including periodicities into the printing type data of an electrophotographic printer, threshold data for forming systematic dot arrays in respective picture- element regions each of which comprises a plurality of picture elements having a mutually coupling relation, are generated from a data generating portion 101 for generating non-periodic data among the respective picture-element regions. Consequently, such printing type data are obtained as to suppress the generation of moire among the respective picture-element regions and have the systematic dot arrays of concentrated dots, etc., in the respective picture- element regions. Also, the propagating processing of the quantization errors to the image data which are generated from the comparisons of the picture data with the threshold data is performed every picture-element region for forming the systematic dot array. As a result, the signal processing amount of the apparatus 100 can be cut down in comparison with the case of performing the propagating processing every picture element.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus, and more particularly to an image forming apparatus for gradationally converting image data containing periodicity into a print format of an electrophotographic printer.

[0002]

2. Description of the Related Art In recent years, the performance of image equipment for inputting, displaying, and outputting images has been remarkably improved. A 12-bit / pixel input scanner, a 10-bit / pixel display, and a 4-bit / pixel output printer are typical examples.

In such an image device, image data is handled in a data format suitable for each gradation reproduction capability. Therefore, for example, when printing image data input by a scanner by a printer, the image data input by the scanner is processed. It is necessary to convert the number of gradations into the number of gradations that can be reproduced by the printer (hereinafter referred to as gradation conversion).

For example, in an electrophotographic printer, a gradation conversion method called a dither method is used. Figure 1
As shown in 0, the dither method uses a dither matrix in which N × N thresholds are arranged, and determines ON / OFF of dots by performing threshold comparison with an image signal.

Generally, since the tone reproduction number of a device such as a scanner or monitor for inputting image data to a printer is higher than the tone reproduction number of a printer, dot ON / OFF is locally turned on by using a dither matrix. The density is adjusted and the number of gradations of the input image is represented in a pseudo manner. Such a dither matrix is roughly classified into a dot concentration type in which dots are regularly concentrated by gradually increasing the threshold value from the center of the matrix, and a dot dispersion type in which the threshold values are randomly arranged.

However, when the number of output gradations is binary (white or black), the electrophotographic printer supplies image data including isolated dots such that one pixel is a black pixel and the surrounding eight pixels are white pixels. Then, the toner is difficult to stably adhere to the photoconductor and the isolated dot portion cannot be printed, so that the gradation of the input data is not reflected in the print result. Therefore, a dot concentrated dither matrix in which black pixels are concentrated in 2 pixels or 4 pixels is used.

A copying machine equipped with a scanner and an electrophotographic printer as shown in FIG. 11 is an example of a device to which image devices having different gradation reproduction capabilities are connected. This copying machine is used for printing data from a personal computer and copying printed matter. Most of the printed materials to be copied have a density change cycle of a light and shade pattern as shown in FIG. This is an image format that matches the printing characteristics of the printing machine and the number of reproduced gradations, and is unique to the printing machine and printer.

When a printed matter having such a gradation pattern period is read by a scanner and gradation conversion is performed for an electrophotographic printer, moire occurs and image quality deteriorates. Moire occurs due to interference between the cycle of the grayscale pattern included in the printed matter and the cycle of the grayscale pattern generated by the dither matrix of the gradation conversion method.

[0009]

As one method for suppressing such moire, Japanese Patent Laid-Open No. 4-104576 is disclosed. This is to reduce the periodicity of the printed matter by adding a low-pass filter before the gradation conversion. However, the cycles included in the printed matter are various, and in order to obtain good results for all the printed matters, it is necessary to determine the cycle included in the printed matter and change the coefficient of the low-pass filter. Therefore, there is a problem that the scale of a circuit used for suppressing moiré becomes large and the processing load also increases.

As another method for suppressing moire,
As disclosed in Japanese Patent Application Laid-Open No. 7-123259, an error diffusion method is applied to the gradation conversion method. The error diffusion method is a gradation conversion method that realizes highly accurate gradation reproduction by performing, for each pixel, a process of propagating a quantization error generated by quantization by a threshold value to unquantized data. is there. However, since the error diffusion method forms isolated dots that cannot be printed by an electrophotographic printer especially in a low-density portion, it is necessary to suppress the isolated dots by combining template processing and other processing. In addition, there is a problem that the circuit scale is increased to prevent the image quality deterioration factor such as the chain texture peculiar to the error diffusion method, and the processing load is also increased.

Further, by using a blue noise mask for the threshold value by the error diffusion method as in "Binarization method and storage medium by threshold matrix error diffusion method" disclosed in Japanese Patent Laid-Open No. 10-150565, the error diffusion characteristic There is also a method for improving various image quality problems. Similar to the error diffusion method, this method also has a problem that isolated dots are generated and are not reflected in the print result.

In view of the above-mentioned problems of the prior art, an object of the present invention is to eliminate moire that occurs when an input image including periodicity is gradation converted in an electrophotographic gradation conversion system. An object of the present invention is to provide an image forming apparatus that reduces the number of isolated dots that are not reflected in the print result. Furthermore, it is to simplify the gradation conversion process and to speed up the process.

[0013]

According to the present invention for achieving the above object, a non-periodic data is generated between adjacent pixel regions and a systematic dot array is generated in the pixel regions. It is characterized in that it is converted into a plurality of threshold value data and a threshold value comparison with image data is performed. As a result, it is possible to suppress moire between the pixel areas and to generate print format data having a systematic dot arrangement that suppresses the occurrence of isolated dots in the pixel areas.

Further, according to the present invention, a threshold value of a blue noise mask, which is normally associated with data on a pixel-by-pixel basis, is associated with a pixel area, and a plurality of threshold value data for forming a systematic dot array in the pixel area is provided. It is characterized in that conversion is performed and threshold value comparison with the image data is performed. This allows
Moire can be suppressed between the pixel regions, and print format data having a systematic dot arrangement that suppresses the generation of isolated dots can be generated within the pixel regions.

Further, the present invention is characterized by utilizing a dither matrix which is aperiodic between threshold regions and which is composed of a plurality of n threshold data for forming a systematic dot array in the threshold regions. To do. Thus, it is possible to suppress moire between the threshold regions and generate print format data having a systematic dot arrangement that suppresses the occurrence of isolated dots within the threshold regions.

Further, according to the present invention, the threshold value of the blue noise mask is made to correspond to the pixel area, and the threshold value of the blue noise mask is converted into a plurality of threshold value data for forming a systematic dot array in the pixel area. It is characterized in that the threshold value comparison with the image data is performed by using the dither matrix arranged as described above. As a result, it is possible to suppress moire between the pixel areas and to generate print format data having a systematic dot arrangement that suppresses the occurrence of isolated dots in the pixel areas.

Further, according to the present invention, the conversion error generated when the print format data is determined by comparing the image data and the threshold data is propagated to the image data which is not quantized in the pixel area unit or the threshold area unit. It is characterized by going. As a result, it is possible to suppress moire generated in the gradation conversion processing only by threshold value comparison and further suppress isolated dots generated due to the propagation of quantization error in pixel units.

Further, according to the present invention, a calculation for obtaining the threshold value is made by previously forming a table of the correspondence relation between the threshold value of the aperiodic data or the blue noise mask and the threshold value corresponding to each pixel in the pixel area. And the threshold data can be obtained at high speed.

According to the present invention, the above-mentioned systematic dot arrangement is reduced by increasing the brightness value or the density value of the image data in the pixel area or the threshold area.
It is characterized by a threshold array in which dots are concentrated.

Further, according to the present invention, a plurality of threshold data for forming a systematic dot array in the pixel region or the threshold region is, for example, non-periodic data TH, the number of pixels in the pixel region or The number of threshold data in the threshold region is N
In the case of, the threshold value used for the quantization of the first pixel is 1 · TH / N,
The threshold used in the second pixel quantization is 2 · TH / N, and the threshold used in the Nth pixel quantization is N · TH / N. It is characterized in that the threshold data is determined by the number of thresholds in the threshold region.

Alternatively, a plurality of threshold data for forming a systematic dot array in the pixel region or the threshold region is, for example, the threshold TH of the blue noise mask,
When the number of pixels in the pixel region or the number of thresholds in the threshold region is N, the threshold value used for the first pixel quantization is TH / N, the threshold value used for the second pixel quantization is 2TH / N, the Nth pixel The threshold value used in the quantization is TH, which is threshold data determined by the threshold value of the blue noise mask and the number of pixels of the pixel area or the threshold number of the threshold area.

Further, according to the present invention, in the correction value determining means, the quantization error of the pixel region or the threshold region is, for example, the number of pixels in the pixel region, or the threshold number n in the threshold region, the pixel region or In the case of the quantization errors E1 to En of the image data corresponding to the threshold area, it is the sum (ΣEn), and the correction value is determined to be 1 / n · ΣE.

Furthermore, the present invention is a method for generating a dither matrix, wherein each threshold value of the blue noise mask is made to correspond to a threshold region composed of a plurality of threshold value data having a connection relationship, and the threshold value of the blue noise mask is set as described above. It is characterized in that a dither matrix is generated by converting into a plurality of threshold data for forming a systematic dot array in the threshold region.

Further, the present invention is a copier, which comprises a scanner section,
A printer unit and a gradation conversion unit for converting image data read by the scanner into print data for printing by the printer unit, wherein the image forming apparatus described above is applied to the gradation conversion unit. I am trying.

According to the present invention as described above, in the image forming apparatus for converting the image data including the periodicity into the data of the printing format of the electrophotographic printer, in the pixel area composed of a plurality of pixels having a connection relation. In, by generating threshold data for forming a systematic dot array from the aperiodic data between the pixel regions, to suppress the occurrence of moire between the pixel regions, in the pixel region, It is possible to obtain a gradation conversion result having a systematic dot arrangement such as dot concentration.

Further, the quantization error generated by the comparison between the image data and the threshold value data is propagated to the image data by the pixel area unit for forming the systematic dot array, thereby propagating in the pixel unit. Compared to the case of processing
The amount of signal processing can be reduced, and the amount of data used for accumulating the quantization error can be reduced. Further, it is possible to suppress moire generated by gradation conversion processing only by threshold comparison and isolated dots generated by error propagation in pixel units.

[0027]

BEST MODE FOR CARRYING OUT THE INVENTION In the embodiment of the image forming apparatus of the present invention, as shown in the image forming apparatus 100 of FIG. 7A, an image input device 76 such as a scanner and an image output device 77 such as a printer are connected. The information processing control device 70 can be installed as hardware.

The information control device 70 comprises a CPU, hardware such as ASIC, memory, and an image input / output interface. Specifically, a CPU 71 that controls input / output of image signals and a control of the image processing apparatus 100, a signal input IF 72 that inputs image data from the image input apparatus 76 to the information control apparatus 70, and accumulation of input image data. And a RAM 73 for storing image processing results, and a ROM 7 for storing parameters and image processing programs used in image processing
4. The image forming apparatus 100 according to the present invention, and the signal output IF 75 for outputting the image processing result to the image output apparatus 77. The image forming apparatus 100 is hardware such as ASIC as described later.

The signal input IF, RAM, ROM, image processing circuit, and signal output IF will be specifically described below.
The signal input IF 72 is an interface such as USB, IEEE1394, Centronics, memory card, PCI, Ethernet or the like, and inputs an image signal from the image input device 76 to the information control device 70. The RAM 73 stores image data such as SDRAM, SRAM, DRAM, memory card, and hard disk, and saves parameters. ROM74 is Flash RO
Parameters such as M handled by the image forming apparatus 100 and CP
The control program used in U71 is stored. The signal output IF75 is USB, IEEE1394,
Centronics, memory card, PCI, Ethernet
It is an interface such as et and outputs the image processing result to the image output device 77.

As shown in FIG. 7B, the image forming apparatus 100 includes an information processing control device 70 to which an image input device 76 such as a scanner and an image output device 77 such as a printer are connected.
0 can be installed as software.

The information control device 700 is composed of a CPU, a memory, and an image input / output interface. Specifically, the input / output control of the image signal and the signal input IF 702 for inputting the image data from the CPU 701 and the image input device 76 to the information control device 700, which executes the functions of the image forming device 100 by software processing, are input. A RAM 703 for accumulating image data and storing an image processing result, a parameter 704 for handling image processing, a ROM 704 storing an image processing program for realizing a function of the image forming apparatus 100 by software processing, and an image output result for an image output apparatus. 77
The signal output IF 705 for outputting to

Hereinafter, the signal input IF and the signal output IF are the same as those shown in FIG.
1, the RAM 703 and the ROM 704 will be specifically described. The CPU 701 executes control of input / output of image signals and functions of the image forming apparatus 100 by software processing. A program for executing software processing is stored in the RAM 703 or RAM 704 described later, and the CPU 701 performs software processing according to this program. RAM703 is SDRAM, S
It stores image data in RAM, DRAM, memory cards, hard disks, etc., and saves parameters. The ROM 74 stores parameters such as a flash ROM handled by the image forming apparatus 100, a control program used by the CPU 71, and an image processing program for realizing the functions of the image forming apparatus 100 by software processing.

As described above, the image forming apparatus 100
Can be realized by hardware or software. Hereinafter, the image forming apparatus 100 will be specifically described with reference to examples.

(Embodiment 1) A first embodiment of the image forming apparatus of the present invention will be described. FIG. 1 shows the configuration of the image forming apparatus. The image forming apparatus 100 has a connection n
For each pixel area formed of a plurality of pixels, the aperiodic data generation unit 101 that generates aperiodic data TH between the pixel areas and the aperiodic data TH so that isolated dots are not generated in the pixel area , A threshold value generation unit 104 configured by a threshold value pattern determination unit 102 that converts the dots into threshold values TH (1 to n) of each pixel that systematically concentrates the dots, and an image signal A (1 to n) in the pixel area. The threshold TH (1 to n)
And a quantization of each pixel and a process of propagating a quantization error generated by the quantization for each pixel region.

FIG. 2 shows details of the multi-pixel gradation converting section. First, the aperiodic data generation unit 101 will be described. The aperiodic data TH generated by the aperiodic data generator 101 is generated between the generated data (THa, THb,
There is no periodicity (between THc). However, since it is difficult to generate data that does not completely include periodicity, pseudo aperiodic data that can be easily created may be used. There are various possible methods for generating the aperiodic data TH, such as a method of generating simple random numbers such as the average sampling method and the mixed congruential method, and a method of using a normal distribution. The method is not limited as long as it has a periodicity.

FIG. 13 shows a relationship between pixels and a pixel area and a threshold value determining method. (x, y) shows the address of the pixel, and (i, j) shows the address of the pixel area when 4 pixels are the pixel area. (I, j) =
THa, THb, and THc are aperiodic data between the pixel regions corresponding to the pixel regions of (0, 0), (0, 1), and (0, 2). For the threshold value in the pixel area, for example, (i,
j) = aperiodic data THa in the pixel region of (0,0)
Decrease the brightness value (black → white) of the image signal and the density value (white →
Due to the increase of (black), the dots within the pixel area are (x, y) =
Convert to a threshold value that occurs in (0,0) → (0,1) → (1,0) → (1,1).

The relationship between the occurrence of dots and the threshold value will be specifically described below. In order to simplify the description, a description will be given using a quantization method of comparing the image signal with a threshold value and determining dots ON and OFF.

The pixel area is a local area of the image, and the image signals in one pixel area have similar brightness values or density values. Therefore, by setting the threshold value of each pixel in the pixel area, It is possible to define the structure of dots in the pixel area formed by quantization. For example, each pixel in the pixel area (x, y) = (0, 0), (0, 1), (1, 0), (1,
The threshold values corresponding to 1) are THa / 4 and 2THa /
4, 3, THa / 4, THa, when the density value of the image signal in the pixel area is THa / 4 or more and less than 2THa / 4, one pixel of (0, 0), the density of the image signal in the pixel area When all values are 2THa / 4 or more and less than 3THa / 4, (0,
0) Two pixels of (0, 1), when the density value of the image signal in the pixel area is 3 THa / 4 or more and less than THa, (0, 0) (0,
1) Three pixels of (1, 0), when the density value of the image signal in the pixel area is THa or more, all pixels in the pixel area can be dot-on to obtain a quantization result.

In this example, as the density of the image signal in the pixel area increases, the dots in the pixel area are changed to (0, 0) →
A threshold array which is formed so as to systematically surround the center of the pixel area (hereinafter referred to as dot concentration) in the order of (0,1) → (1,0) → (1,1) Is.

In another example, the threshold value of each pixel in the pixel area is 2THa / 4, 2THa / 4, THa,
In the case of THa, when the density value of the image signal in the pixel region is 2THa / 4 or more and less than THa, (0,0) (0,
2) in 1), and when the density value of the image signal in the pixel area is THa or more, 4 vertical pixels such as (0,0) (0,1) (1,0) (1,1) It is also possible to systematically concentrate the dots connected to the pixels in two steps.

By using the array of threshold values in this way, it is possible to perform quantization while suppressing the occurrence of isolated dots, and it is possible to form the optimum dots for printing by the printer within the pixel area. Since the optimum dot shape for printing by the printer largely depends on the printing characteristics of the printer, if the array of thresholds is such that dots are systematically formed in the quantization in the pixel area, the above example is used. It is not limited.

The threshold value is set in advance from THa / 4, 2THa / 4, 3THa / 4, based on the values that the aperiodic data can take.
The threshold value of each pixel in the pixel area corresponding to each aperiodic data such as THa is obtained in advance, and the input / output relationship is tabulated.

FIG. 15 shows a table used in the threshold pattern determining section. The threshold to be set can also be obtained by referring to a table without calculating the threshold corresponding to each pixel in the pixel area from the aperiodic data.

However, when the range of data generated from the aperiodic data generator 101 is different from the data range that the input signal can take (for example, aperiodic data 16 bits, input signal 8 bits), the comparison with the input signal is made. Since it cannot be performed, a process of changing the data range of the aperiodic data to the data range of the input signal (for example, 16 bits of aperiodic data → 8 bits) by using a bit shift process or the like before and after determining the threshold pattern. I do.

Next, the multi-pixel gradation conversion unit 103 will be described. The multi-pixel gradation conversion unit 103 uses the threshold value from the threshold pattern determination unit 102 to convert the gradation of each pixel. Using FIG. 2, the plural-pixel gradation conversion unit 103
Will be specifically described.

The multi-pixel gradation conversion unit 103 performs signal correction of each pixel on the input signals A (1) to A (n) of each pixel in the pixel area and outputs B (1) to B (n). Output signal correction unit 20
0, B (1) to B (n) are compared with the threshold values TH (1) to TH (n) from the threshold pattern determination unit 102, and the output signal C
(1) to C (n), and further, a quantization unit 201 that outputs a quantization error D (1) to D (n) of each pixel caused by the quantization, a pixel region from the quantization unit 201 Error amount determining unit 202 that calculates and outputs the quantization error E in the pixel region from the quantization error D (1) to D (n) of each pixel in the pixel, and the quantization in the pixel region from the error amount determining unit 202 The data storage unit 20 that temporarily stores the error E and outputs the quantization error E ′ in the pixel region requested by the signal correction unit 200.
It is composed of three. Hereinafter, the signal correction unit 200, the quantization unit 201, the error amount determination unit 202, and the data storage unit 20.
3 will be specifically described.

The signal correction unit 200 utilizes the quantization error E'generated in the pixel region subjected to the quantization processing to input signals A (1) to A (A) of the pixel region not subjected to the quantization processing.
B (1) to B (n) are calculated by adding corrections to (n).

FIG. 14 shows a signal correction method. here,
(i, j) = (0,0), (1,0), (2,0), ~
(0, 1) indicates a pixel area that has been quantized.
Also, E '(0,0), E' (1,0), E '(2,
0), to E ′ (0,1) represent the error E ′ in the pixel area caused by the quantization of each pixel area. The error E ′ in such a pixel area is stored in the data storage unit 203. Error in pixel area E '
The error amount determination unit 202 will describe the method of generating the.

The signals A (1) to A (4) of the pixels in the pixel region (i, j) = (1,1) are corrected to obtain B (1) to B (1)
The method of obtaining (4) is shown in equation (1).

B (k) = A (k) + e (1) e = (E '(1,0) * P1 + E' (0,1) * P2) / n P1 + P2 = 1.0 n = in pixel area , K = (1 to n), where e is the amount of error added to each pixel in the pixel area, n is the number of pixels in the pixel area, and P1 and P2 are quantization errors from two pixel areas. It shows the error coefficient that determines what kind of allocation is used.

In this way, by propagating the quantization error of the pixel region generated by the quantization processing to the signal of the pixel area which is not subjected to the quantization processing, the gradation of the input signal can be preserved. it can. It should be noted that in the equation (1), the quantization error of the pixel area used is set to two places.
(0,0), E '(1,0), E' (0,1), E '(2,0)
Such a wide range of pixel region quantization errors may be used. The number of pixel regions used for signal correction and the setting of the error coefficient need to be changed according to the target image quality, and thus are not limited.

The quantizing unit 201 includes a threshold pattern determining unit 1
Threshold value TH corresponding to each pixel in the pixel area from 02.
(1) to TH (n) are compared with the correction data B (1) to B (n) of each pixel in the pixel area from the signal correction unit 200,
The output signals C (1) to C (n) are quantized. In addition, the quantization error D in each pixel caused by the quantization
(1) to D (n) are output to the error amount determination unit 202. For example, when the 8-bit (0-255) input signal A (n) signal is converted into a 1-bit (0 or 1) output signal C (n) by gradation conversion,
The method of obtaining C (n) and D (n) from B (n) is as in equation (2).

[0053]   IF (B (k)> TH (k)) {C (k) = 1; D (k) = B (k) −255}   ELSE {C (k) = 0; D (k) = B (k)} (2) Here, n is the number of pixels in the pixel region, and k is 0 to n.

FIG. 16 shows data of each part of the multi-pixel conversion part. (a) is data when the number of pixels in the pixel area is four, (b) is a threshold value assigned to each pixel, (c) is data quantized from the threshold value, (d) is a quantization error of each pixel An example is shown. Formula (2) will be described using B (1) and B (3) as an example.

B (1) (= 120) is the threshold TH (1)
Since it is larger than (= 50), the 8-bit signal is quantized into a 1-bit signal 1 corresponding to 255. But B
Since (1) (= 120) is not equivalent to 255, the quantization error D (1) (= -135) generated during quantization is B
It can be calculated by (1) -255.

B (3) (= 126) is the threshold TH (3)
Since it is smaller than (= 150), the 8-bit signal is quantized into a 1-bit signal 0 corresponding to 0. However, B (3)
Since (= 126) is not equivalent to 0, the quantization error D (3) (= 126) generated at the time of quantization can be obtained by B (3) -0.

As a result, each pixel in the pixel area can be quantized, and the quantization error of each pixel generated by the quantization can be generated.

Next, the error amount determination unit 202 will be described. The error amount determination unit 202 determines the quantization error D (1) to D (D) generated by the quantization of each pixel in the pixel area in pixel area units.
The quantization error E in the pixel area is obtained from (n). The quantization error E in the pixel area can be obtained by the equation (3). k: 1 to n.

E = ΣD (k) (3) Equation (3) is the result of obtaining the sum of the quantization errors D (1) to D (n) generated by the quantization of each pixel in the pixel area, This is the quantization error E in the pixel area. The result obtained by Expression (3) is output to the data storage unit 203 for use by the signal correction unit 200.

Next, the data storage unit 203 will be described. The data storage unit 203 sequentially stores the quantization error E in the pixel area from the error amount determination unit 202. Also,
The signal correction unit 200 outputs the quantization error E ′ in the pixel area used for signal correction.

With the above configuration, the image forming apparatus of this embodiment performs gradation conversion on the input signals A (1) to A (n) of each pixel in the pixel area and outputs the output signals C (1) to A (n). C (n) can be output.

The signal correction unit 200 and the error amount determination unit 2
The calculation method of 02 is not limited to equations (1) and (3). Similar results can be obtained even if the sharing of the calculation of each part is changed depending on the parameter such as the coefficient used in each part. For example, P of the equation (1) used in the signal correction unit 200
When 1 and P2 are 0.5 respectively, formula (4),
Even if the result of (5) is used, the equivalent B (n) can be generated, and as a result, the calculation amount can be reduced.

E = 0.5 * ΣD (k) (4) B (k) = A (k) + e (5) e = (E '(1,0) + E' (0,1)) / n Here, n = the number of pixels in the pixel region and k = 0 to n.

FIG. 8 shows a method of propagating the quantization error in the pixel area of the gradation conversion method. The above-described multi-pixel gradation conversion unit 103 is the minimum average error method shown in FIG. When the error in the pixel area due to the quantization is once stored and the pixel area at the X position is quantized
By using the aggregated value of, the quantization error generated in the peripheral pixel area is made small on average,
It is applied to gradation conversion in the pixel area.

On the other hand, in the error diffusion method shown in FIG. 8B, the quantization error amount of the pixel area (position of X) determined by the error determining unit 202 is distributed in advance to the pixel area to be corrected. The data is stored in the data storage unit 203. Even if such an error diffusion method is applied to gradation conversion, the same result can be obtained.
As described above, the method of feeding back the quantization error in the pixel area is not limited as long as the above-described gradation conversion result can be obtained.

The function of the image forming apparatus 10 described above is
It can also be realized by software. Software processing similar to that of the image forming apparatus 100 can be executed by a processor such as a microcomputer. Hereinafter, a method for realizing the functions of the image forming apparatus 100 of the present invention by software processing will be described.

FIG. 9 is a flowchart showing the processing method of the information processing control device 700. (A) is an example in which the average error minimum method is used for the error propagation in the pixel area, and (b) is an example in which the error diffusion method is used for the error propagation in the pixel area. First, the average error minimum method will be described.

After inputting the signal A (n) of the pixel in one pixel area (9001), the error amount E'generated by the quantization of the peripheral pixel area from the data storage unit such as the hard disk or the memory is used as the error coefficient P1, Aggregated by the ratio of P2, A (n)
The data e to be added to each pixel of is calculated (9002). Add e to the input signal A (n) and output the signal B (n) (900
3).

Next, aperiodic data TH is generated between the pixel areas (9004). This aperiodic data is converted into a threshold value TH (n) of each pixel that induces dot generation (9005). Then, the signal B and the threshold value of the pixel are compared and quantized, and the quantized value C (n) of each pixel in the pixel area is quantized.
(9006). Further, the quantization error D (n) of each pixel generated by the quantization is obtained (9007). The quantization error D (n) of each pixel is totaled to obtain the error E in the pixel area (9008), and the quantization error E is stored in the data storage unit (9009). The above processing is performed until the image data ends for each pixel area.

Next, description will be made regarding the case where the gradation conversion of the pixel area is performed by using the error diffusion method in the pixel area.
After inputting the signal A (n) of the pixel in one pixel area (901
1) The error E ′ accumulated in the data area indicating the position of the pixel area to be quantized in the data storage unit is converted into an error e added to each pixel (9012). The error e is added to the input signal A (n) and B (n) is output (9013).

Next, aperiodic data TH is generated between the pixel areas (9014). This aperiodic data is converted into a threshold value TH (n) for each pixel that induces dot generation (9015). Then, the signal B and the threshold value of the pixel are compared and quantized to obtain the quantized value C (n) of each pixel in the pixel area (9016).

Further, the quantization error D (n) of each pixel generated by the quantization is obtained (9017). The error E in the pixel area is obtained from the quantization error D (n) of each pixel, and the errors E1 and E2 to the pixel area using the error E are calculated as error coefficients P1 and P2.
Is used to determine (9018). Then, the errors E1 and E2 are added to the data area indicating the position of the pixel area in the data storage (9019). The above processing is performed until the image data ends for each pixel area.

As described above, in the image forming apparatus of the present embodiment, in the image forming apparatus for converting the image data including the periodicity into the print format of the electrophotographic printer, from the plurality of pixels having the connection relationship, By generating threshold data for forming a systematic dot array from the aperiodic data between the pixel regions in the pixel region,
It is possible to suppress the occurrence of moire between the pixel areas and obtain gradation conversion having a systematic dot arrangement such as dot concentration in the pixel areas.

Further, the propagation processing of the quantization error generated by the comparison of the image data and the threshold data to the image data is carried out in the pixel area unit for forming a systematic dot array, so that the propagation processing is carried out in the pixel unit. As compared with the case of performing, the signal processing amount can be reduced, and the data capacity used for accumulating the quantization error can be reduced. Further, it is possible to suppress moire generated by gradation conversion processing only by threshold comparison and isolated dots generated by error propagation in pixel units.

(Embodiment 2) Next, a case where the data generated from the aperiodic data generator 101 of the image forming apparatus described in Embodiment 1 is used as the threshold value of the dither matrix used in the blue noise mask method explain.

FIG. 3 shows the structure of the image forming apparatus according to the second embodiment. Since only a part that generates a threshold is different from the first embodiment, only a part having a difference from the image processing apparatus in FIGS. 1 and 2, that is, the threshold generation unit 300 will be described.

The threshold value generating section 300 is a blue noise mask storage section 301 for storing a dither matrix (hereinafter referred to as a blue noise mask) used in the blue noise mask method.
The threshold pattern determination unit 302 is configured.

Blue noise is noise that does not have a low frequency component but has a high frequency component. The dot ON / OFF pattern generated by the threshold comparison of the blue noise mask is asymmetric in a non-periodic and radial manner. In the frequency characteristic, the low frequency power spectrum is small and the image power spectrum is in the high frequency region. focusing. This is dot ON / generated by the error diffusion method described in the conventional example.
It is given by the analysis in the spatial frequency of the OFF pattern.

An example of quantization using the blue noise mask will be described with reference to FIG. The blue noise mask has a size (256 × 256 pixels in the example of FIG. 17) relatively larger than that of the dither matrix used for the dot concentration type or dot dispersion type described above in order to suppress the occurrence of periodicity. It When the pixel size of the image data is equal to or larger than the size of the blue noise mask, one blue noise mask is allocated in a tile shape as shown in the figure, and the threshold value of the blue noise mask corresponding to each pixel is determined.

For example, if the pixel address of the image data is (a,
b) (0 ≦ a <256, 0 ≦ b <256), the threshold value TH (a, b) of the corresponding blue noise mask is matrix [a] [b].
(= Matrix [a% 256] [b% 256]) and the pixel address is (c, d) (256 ≦ a <512, 256 ≦ b <512), TH
(c, d) is matrix [c-256] [d-256] (= matrix
[C% 256] [d% 256]). In this way, quantization is performed by comparing the threshold values of the Bounoise mask corresponding to the address of the image data.

The reason why the blue noise mask having such characteristics is used for the quantization of the pixel area is the effect of suppressing the moire of the image signal, as in the case of the aperiodic data described in the first embodiment. Because there is. Further, it is because the blue noise effect suppresses a factor of image quality deterioration including a lot of low frequency components such as a chain texture generated by the propagation processing of the quantization error and a fingerprint texture generated at a specific gradation value.

However, if the blue noise mask is directly quantized in correspondence with the image signal, an isolated dot having a high frequency power spectrum is generated as described above, so that a high frequency component exists between the pixel regions, The threshold value generation unit 300 generates a threshold value for forming a systematic dot array such that dots are concentrated in the pixel area. The operation of the threshold value generator 300 will be specifically described below.

The blue noise mask storage unit 301 stores the blue noise mask as described above. The threshold pattern determination unit 302 acquires the threshold value of the blue noise mask assigned to one pixel region from the blue noise mask storage unit 301 from the pixel address of the image data or the address of the pixel region. Specifically, when the size of the blue noise mask is M × N pixels (matrix [M] [N]), the pixel address of the image data is (a, b), and the number of pixels in the pixel area is 1 × m pixels, The threshold value of the blue noise mask assigned to the pixel area can be obtained by the equation (6).

TH = matrix [(a / l)% M] [(b / m)% N] (6) The threshold value corresponding to one pixel region thus obtained is the threshold value described in the first embodiment. Similar to the pattern determination method, the threshold value of each pixel in the pixel area is converted.

As described above, by using the blue noise mask for the threshold value of the pixel area composed of a plurality of pixels that enables control of the dot generation pattern such as the dot generation order and the dot generation position, It is possible to suppress the occurrence of moire between pixel regions.

Regarding the threshold value of each pixel in the pixel area, the threshold value of the blue noise mask is used to convert it into a threshold value at which dots are systematically concentrated. Using this threshold value, each pixel in the pixel area is quantized, and the quantized result is output. Further, the process of propagating the quantization error generated by the quantization to the image signal is performed for each pixel region.

By performing such gradation conversion, a systematic dot arrangement such as dot concentration is formed in the pixel area, and the generation of moire is suppressed between the pixel areas due to the effect of blue noise. Data can be formed.

Further, by performing the propagation process of the quantization error generated by the comparison of the image data and the threshold value data to the image data, the moiré generated by the gradation conversion process only by the threshold value comparison and the pixel unit are performed. It is possible to suppress the isolated dots that occur in the error propagation processing of, and further reduce the signal processing amount and the data capacity used for accumulating the quantization error compared to the case where the propagation processing is performed in pixel units. You can

Note that the blue noise effect also reduces the factors of image quality deterioration that include many low-frequency components, such as the chain-like texture that occurs in the quantization error propagation processing and the fingerprint-like texture that occurs at a specific gradation value. be able to.

Further, it can be realized by software processing as in the first embodiment. In this case, FIG.
A non-periodic data generation step 9004 in (b),
9014 is for determining the threshold position of the blue noise mask,
The threshold may be acquired from the blue noise mask.

(Third Embodiment) Next, a third embodiment in which the threshold value generated in the threshold value generating unit 300 of the image forming apparatus described in the second embodiment is used for the gradation conversion of the image data by using the dither matrix is used. An example will be described.

FIG. 4 shows an image forming apparatus according to the third embodiment. Since only a part that generates a threshold value is different from FIG. 3, only a part having a difference from the image forming apparatus according to the second embodiment, that is, the threshold value generation part 400 will be described.

The threshold generator 400 converts the threshold output from the threshold generator 300 of the second embodiment into a dither matrix (hereinafter referred to as dot control type blue noise mask), and stores the dot control type blue noise mask in the dither matrix storage unit 40.
1 and a threshold value determination unit 402 that extracts the threshold value of the dot control type blue noise mask corresponding to the pixel address of the image data from the dither matrix storage unit 401 and outputs the threshold value to the multiple pixel gradation conversion unit 103.

FIG. 18 shows an example in which the blue noise mask is converted into a dot control type blue noise mask. This is a dot control type blue noise mask when the blue noise mask of M × N pixels is m × n pixels in the pixel area. Pixel area is l
Since it is × n pixels, the pixel size of the dot control type blue noise mask is m · M × n · N. 2 × described in Example 1
By using the threshold value determination pattern in the case of a pixel area of 2 pixels, when the threshold value of matrix [0] [0] of the blue noise mask is a, the dot control type blue noise mask co_matr
ix [0] [0] is a / 4, co_matrix [0] [1] is a / 2, c
o_matrix [1] [0] is 3a / 4, co_matrix [1] [1]
Becomes a. When the threshold value of matrix [M] [N] is b, co_matrix [m ·
M] [n ・ N] is b / 4, co_matrix [m ・ M] [n ・ N + 1]
Is b / 2, co_matrix [m · M + 1] [n · N] is 3b / 4
co_matrix [m · M + 1] [n · N + 1] becomes b.

FIG. 19 shows a flowchart of the dot control type blue noise mask generation method. First, a blue noise mask matrix [x] [y] of x × y pixel size is generated (1901). Next, the sizes m and n of the pixel area are determined (190
2). Initializing the y-axis (1903) and initializing the x-axis (1904). Next, blue noise mask matrix [x] [y]
The threshold TH of is taken out (1905). The TH is used to convert the threshold pattern TH (0,0) to TH (1,1) in the pixel area (90
6). The threshold patterns TH (0,0) to TH (1,1) are set to dot control type blue noise masks co_matrix [m * x] [n * y] to co_
It is saved in the matrix [m * x + 1] [n * y + 1] (1907). Next, the x-axis is counted (1908), and the x-axis end determination is performed (1908). Next, the y-axis is counted 1910, and the y-axis end determination is performed (1911). By performing the above processing for all the threshold values of the blue noise mask matrix [x] [y], it is possible to create a dot control type blue noise mask of a pixel size m · M × n · N.

The dot control type blue noise mask generated by such a procedure may be registered in the RAM or ROM as shown in FIG. 7 as an initial setting of the image processing apparatus.

As described above, in the third embodiment, the dither matrix corresponding to each pixel in the pixel area generated by the blue noise mask is used to quantize each pixel in the pixel area, and the quantization result is obtained. Output. Further, the quantization error in the pixel area generated by the quantization is propagated to the other non-quantized pixel area.

By performing such gradation conversion, the size of the dither matrix becomes larger than that of the blue noise mask described in the second embodiment, but a threshold value corresponding to each pixel in the pixel area is generated for each pixel area. Because you don't have to
High-speed processing becomes possible. Further, due to the effect of blue noise, it is possible to suppress the occurrence of moire between pixel regions and form print-type data having a systematic dot arrangement such as dot concentration in the pixel regions.

Further, the quantization error generated by the comparison between the image data and the threshold value data is propagated to the image data in the unit of pixel area, so that the moire generated in the gradation conversion process only by the threshold value comparison and the pixel unit are performed. It is possible to suppress the isolated dots that occur in the error propagation processing of, and further reduce the signal processing amount and the data capacity used for accumulating the quantization error compared to the case where the propagation processing is performed in pixel units. You can

It should be noted that the blue noise effect can also be used to reduce the factors of image quality deterioration that include many low-frequency components, such as the chain-like texture that occurs in the above-described quantization error propagation processing and the fingerprint-like texture that occurs at a specific gradation value. You can

Further, it can be realized by software processing as in the first embodiment. In this case, FIG. 9 (a),
(B) Aperiodic data generation steps 9004 and 901
4 can be realized by determining the threshold position of the dot control matrix and acquiring the threshold from the dot control matrix.

(Fourth Embodiment) In the first to third embodiments, the case of handling a monochrome image has been described. In the fourth embodiment, a case where the image forming apparatus shown in the first to third embodiments is applied to gradation conversion of a color image will be described.

FIG. 20 is a block diagram of an image forming apparatus for converting the gradation of a color image. Basically, since gradation conversion is performed independently for each color, the processing of the multi-pixel gradation conversion unit 103 described in the first to third embodiments is performed for the number of colors. The multi-pixel gradation conversion unit 103 may be provided in parallel for the number of colors as shown in FIG. 20, or the multi-pixel gradation conversion unit 103 for one color sequentially performs gradation conversion for the number of colors. Good. In this embodiment,
A threshold value control unit 2002 is provided that assigns the threshold value from the threshold value generation unit 2001 to the multi-pixel gradation conversion unit 103 for each color. Hereinafter, the threshold value generating unit 2001 will be described with reference to Examples 1 to 3.
Since the threshold generator described in 1 can be used, the threshold controller 2002 will be specifically described.

The image signals R (k), B (k), G (k), and k = 1 to n of the pixel area of each color composed of n pixels are the same as those described in the first to third embodiments. The gradation conversion of the area is independently performed, and the signals R ′ (k), B ′ (k) after the gradation conversion,
Output G '(k). However, regarding the threshold value used in the quantization of each pixel, the threshold value from the threshold value generation unit 2001 needs to be assigned to the threshold value of each color by the threshold value control unit 2002.

FIG. 21 shows the configuration of the threshold controller 2002. The threshold controller 2002 controls the threshold generator 2001. For example, as shown in FIG. 21 (a), the threshold value generation unit 2002 generates threshold values TH (k), k = 1 to n corresponding to each pixel in the pixel area in units of each pixel area, and the threshold values TH (k) and k = 1 to n are generated for each color image. Similar threshold TH (k) = THR (k) =
THG (k) = THB (k) and k = 1 to n are assigned threshold control.

Alternatively, as shown in FIG. 21 (b), the threshold value generation unit 2002 detects the threshold values THR (k), THG (k), THB in the pixel regions in each pixel region unit and each color unit.
(K), k = 1 to n are generated, and different thresholds THR (k), THG (k), THB (k), k = are generated for each color image.
Threshold control for assigning 1 to n is performed.

An example of a method of assigning different thresholds is a method of using dither matrixes having different threshold arrangements of three colors when the dither matrix is used in the threshold generators described in the second and third embodiments, and FIG. As shown, this can be realized by a method of shifting the application position of the dither matrix to the image data for each color by using the dither matrix of one color.

As described above, the image forming apparatus of the present invention can be applied to tone conversion of color images.

(Fifth Embodiment) Next, a fifth embodiment in which the image forming apparatus of the present invention is installed in a copying machine will be described. Figure 5
Is a scanner unit 501 that reads a copy and converts it into image data, a resolution conversion unit 502 that changes the size of the image data based on the user's request or the printing resolution of the printer unit, and the input RGB three-color image signals are the toner colors of the printer. A color conversion unit 503 for converting into a signal, a gradation conversion unit 504 for converting the number of gradations of each color signal into a number of gradations printable by a printer, and an electronic device for printing on a medium such as paper using the result of gradation conversion. The image forming apparatus of the present invention is applied to the gradation converting unit 504, which is constituted by a photographic printer unit 505. Hereinafter, each part will be specifically described.

The scanner section 501 irradiates the copy with light,
It is a device that reads the intensity of the reflected light and forms image data of a copy. A general scanner forms image data of 8 bits / color per pixel, but in recent years, there is a scanner which acquires 8 bits / color or more in order to perform correction processing on the read image data. The resolution conversion unit 502 receives a resizing request from the user such as A3 size → A4 size,
In consideration of the print resolution of the printer unit 505, the scanner unit 5
The image data from 01 is enlarged and reduced. For example, the scanning resolution of the scanner is 200 DPI
In the case where the printer resolution is 400 DPI and the user does not request resizing, the copy result of the same size as the original cannot be output unless the image data is doubled vertically and horizontally. Also, with the same device, 1/16
When there is a request for resizing, it is necessary to reduce the image data to 1/2 in both vertical and horizontal directions.

There are various resolution conversion methods such as the nearless tray bar method and the bilinear method, but the present embodiment is not limited to this.

The color conversion section 503 converts the data from the resolution conversion section 502 into color signals of ink used in the printer section 505. Regarding the color conversion method, the scanner unit 501
There are various methods such as a method of using a table in which the color characteristics of the printer unit 505 are used and a method of using a matrix operation, but the present embodiment is not limited to this.

The gradation converting unit 504 converts the number of gradations of each color after color conversion into the number of gradations printable by the printer unit 505, and the image forming apparatus of the present invention as described in the fourth embodiment. Apply.

In the electrophotographic printer, as described in the prior art, the toner stabilizes on the photoconductor even if image data including isolated dots such as one pixel being a black pixel and the surrounding eight pixels being a white pixel is supplied. However, there is a problem that the gradation of the input data is not reflected in the print result because the isolated dot portion cannot be printed. Therefore, as shown in FIG. 13, a threshold value is set such that dots are systematically concentrated in the pixel area. This can reduce the generation of isolated dots. Further, regarding moire generated due to the cycle of the density pattern included in the copy object, quantization in the pixel area is performed using data having an aperiodic property between the pixel areas, and The error generated by the quantization can be suppressed by the effect of propagating to the other non-quantized pixel region.

Regarding the number of gradations that can be printed by the printer unit 505, a binary output of 1 bit / pixel or 2 bits / pixel is used.
The image forming apparatus of the present invention can cope with any number of print gradations, though there are various types such as pixels and multi-value output such as 16 bits / pixel.

In the first to fourth embodiments, the case where the number of output gradations of the image output device is binary has been described. However, by changing the threshold value according to the number of printable gradations, it is also applied to multi-value output. be able to. Specifically, the range of the threshold value generated by the threshold value generation unit is changed according to the number of output gradations of the image output device. For example, in the case of 8-bit input and 1-bit output, quantization is performed to 0, 1 (equivalent to 0, 255 in 8 bits) by setting the threshold value range from 0 to 255. In the case of 2-bit output, 0, 1, 2, 3 (8-bit 0, 85, 17
(Corresponding to 0, 255) can be quantized.

Regarding the resolution conversion unit 502, the color conversion unit 503, and the gradation conversion unit 504 described above, each unit is a hardware circuit like the image forming apparatus 100 in the information processing control unit 70 shown in FIG. 7A. It can also be installed in a copying machine. Further, as in the information processing control device 700 shown in FIG. 7B, the CPU 701 causes the image forming device 100 to operate.
It can also be installed in a copier that has the function of.

As described above, by applying the image forming apparatus of the present invention to the gradation converting section of a copying machine, it is possible to form data in a print format in which the generation of moire and isolated dots is suppressed, and the printing of the printer section is performed. Also in the result, the gradation property of the image data before the gradation conversion process can be maintained. Further, the gradation conversion as described above can be realized at high speed.

[0119]

According to the image forming apparatus of the present invention, threshold value data for forming a systematic dot array in a pixel region composed of a plurality of connected pixels is aperiodic data or the like between the pixel regions. The effect of suppressing the generation of moire between the pixel areas and obtaining data of a print format having a systematic dot arrangement such as dot concentration in the pixel areas is obtained by generating the data.

Further, the propagation processing of the quantization error generated by the comparison between the image data and the threshold data to the image data is carried out in the pixel area unit for forming the systematic dot array, so that it is propagated in the pixel unit. The amount of signal processing can be reduced as compared with the case where processing is performed, and the data capacity used for accumulating the quantization error can also be reduced. Furthermore, it is possible to suppress moire generated by the gradation conversion processing only by threshold comparison and isolated dots generated by error propagation in pixel units.

[Brief description of drawings]

FIG. 1 is a block diagram showing a first embodiment of an image forming apparatus of the present invention.

FIG. 2 is a block diagram showing a detailed configuration of the first embodiment.

FIG. 3 is a block diagram illustrating an image forming apparatus according to a second exemplary embodiment.

FIG. 4 is a block diagram illustrating an image forming apparatus according to a third exemplary embodiment.

FIG. 5 is a block diagram of a copying machine to which the image forming apparatus of the present invention is applied.

FIG. 6 is an explanatory diagram showing a method of shifting the phase of a dither matrix.

FIG. 7 is a configuration diagram of hardware and software that realizes the image forming apparatus.

FIG. 8 is an explanatory diagram of a method of propagating a quantization error in a pixel region of a gradation conversion method.

FIG. 9 is a flowchart showing a procedure of gradation conversion processing according to an embodiment of the present invention.

FIG. 10 is an explanatory diagram of a dither method.

FIG. 11 is a schematic configuration diagram of a conventional copying machine.

FIG. 12 is an explanatory diagram showing a cycle of a density pattern included in a printed matter.

FIG. 13 is an explanatory diagram showing the relationship between pixels, pixel regions, and threshold values.

FIG. 14 is an explanatory diagram showing a method of propagating a quantization error in a pixel area.

FIG. 15 is a configuration diagram of a table used in a threshold pattern determination unit.

FIG. 16 is an explanatory diagram showing an image signal, a threshold value, a quantization result, and a quantization error.

FIG. 17 is an explanatory diagram showing correspondence between pixel addresses of image data and threshold values of dither matrix.

FIG. 18 is an explanatory diagram showing a method of generating a dither matrix having a threshold value of each pixel in a pixel region from a blue noise mask.

FIG. 19 is a flowchart for generating a dither matrix having a threshold value for each pixel in a pixel area from a blue noise mask.

FIG. 20 is a block diagram showing an image forming apparatus of the present invention adapted to color images.

FIG. 21 is an explanatory diagram showing the operation of the threshold controller of FIG. 20.

[Explanation of symbols]

100 ... Image processing device, 102 ... Threshold pattern determination unit,
103 ... Multi-pixel gradation conversion unit, 104 ... Threshold value generation unit, 2
00 ... Signal correction unit, 201 ... Quantization unit, 202 ... Error amount determination unit, 203 ... Data storage unit, 300 ... Threshold value generation unit,
301 ... Blue noise mask storage unit, 302 ... Threshold pattern determination unit, 400 ... Threshold generation unit, 401 ... Dither matrix storage unit, 402 ... Threshold determination unit, 501 ... Scanner unit, 502 ... Resolution conversion unit, 503 ... Color conversion unit , 504
... gradation conversion unit, 505 ... printer unit, 70 ... information processing control device, 71 ... CPU, 72 ... signal input IF, 73 ... R
AM, 74 ... ROM, 75 ... Signal output IF, 76 ... Image input device, 77 ... Image output device, 700 ... Information processing control device, 701 ... CPU, 702 ... Signal input IF, 703
... RAM, 704 ... ROM, 705 ... Signal output IF, 2
001 ... Threshold generator, 2002 ... Threshold controller.

   ─────────────────────────────────────────────────── ─── Continued front page    F-term (reference) 2C262 AA04 AA24 BB01 BB06 BB22                       BB27                 5B057 CA08 CA16 CB07 CB16 CE11                       CE13 CH07                 5C077 LL03 LL18 NN09 PQ20 RR09                       RR11 TT03

Claims (16)

[Claims] 1. An image forming apparatus for converting image data containing periodicity into a printing format of an electrophotographic printer, wherein each pixel area consisting of a plurality of pixels in the connection relationship of the image data has an adjacent relationship. An aperiodic data generating means for generating aperiodic data with respect to a certain pixel region, and a threshold value for converting the aperiodic data into a plurality of threshold value data for forming a systematic dot array in the pixel region. An image forming apparatus comprising: a determination unit and a gradation conversion processing unit that performs gradation conversion processing by comparing the image data with the threshold data. 2. The threshold value determination means according to claim 1, wherein the threshold value of aperiodic data is input, and the threshold value corresponding to each pixel in the pixel region generated from the aperiodic data is output. An image forming apparatus, which is provided with a table indicating the relationship. 3. The threshold data for forming the systematic dot array according to claim 1, wherein the threshold data is non-periodic data TH, and the number of pixels in the pixel region is
In case of N, the threshold value used for the first pixel quantization is 1 · TH
/ N, the threshold used in the second pixel quantization is 2 · TH / N, N
An image forming apparatus characterized in that a threshold value used for quantization of a pixel is N · TH / N and is determined by aperiodic data and the number of pixels. 4. An image forming apparatus for converting image data including periodicity into a print format of an electrophotographic printer, and a blue noise mask storage unit for storing a blue noise mask, and each threshold value of the blue noise mask. A threshold value for converting the threshold value of the blue noise mask into a plurality of threshold value data for forming a systematic dot array in the pixel area. An image forming apparatus comprising: a determination unit and a gradation conversion processing unit that performs gradation conversion processing by comparing the image data with the threshold data. 5. The threshold value determining means according to claim 4, wherein the threshold value of the blue noise mask is input, and the threshold value corresponding to each pixel in the pixel region generated from the threshold value of the blue noise mask is output. An image forming apparatus, which is provided with a table indicating a relationship. 6. The threshold data for forming the systematic dot array according to claim 4 or 5, wherein the threshold of the blue noise mask is TH, and the threshold number is
In the case of N, the threshold value used for the quantization of the first pixel is TH / N,
An image forming apparatus characterized in that the threshold value used for quantization of the second pixel is 2TH / N and the threshold value used for quantization of the Nth pixel is TH, which is determined by the threshold value of the blue noise mask and the threshold number. . 7. The gradation conversion processing unit according to claim 1, wherein the gradation conversion processing unit compares the image data with the threshold value data and converts the image data into the print data, and each of the pixel regions. Correction value determining means for determining the quantization error generated by the quantization, and for determining the correction value for applying the correction to the image data corresponding to the non-quantized pixel region, and storing the correction value. An image forming apparatus comprising: a data storage unit; and a data correction unit that uses the accumulated correction value to correct image data corresponding to a pixel region that has not been quantized. 8. The correction value determining means according to claim 7, wherein the number of pixels in the pixel region is n, and the quantization error of image data corresponding to the pixel region is E1 to En.
In the case, the image forming apparatus is characterized in that the sum of E1 to En is a quantization error of the pixel area, and the correction value is 1 / n · ΣEn, which is determined by the number of pixels n. 9. An image forming apparatus for converting image data including periodicity into a print format of an electrophotographic printer, using a dither matrix in which a plurality of threshold regions each having a plurality of threshold data having a connection relationship are arranged. , A gradation conversion processing unit that performs gradation conversion by comparing the image data and threshold data of the dither matrix, and each threshold data in the threshold region has a systematic dot array in the threshold region. The image forming apparatus is characterized in that the dither matrix that is the threshold data for forming and that extracts only the largest threshold data in the threshold region is aperiodic between the threshold data that are adjacent to each other. 10. The threshold data for forming the systematic dot array according to claim 9, wherein the threshold data is non-periodic data TH, and when the threshold data number of the threshold region is N, the first pixel The threshold used for quantization is 1 · TH / N, and the threshold used for second pixel quantization is 2 · TH.
/ N, the threshold value used in the Nth pixel quantization is N.TH/N, and is determined by the aperiodic data and the threshold number. 11. An image forming apparatus for converting image data including periodicity into a printing format of an electrophotographic printer, using a dither matrix in which a plurality of threshold regions each having a plurality of threshold data having a connection relation are arranged. A gradation conversion processing unit that performs gradation conversion by comparing each pixel of the image data with each threshold value data of the dither matrix, wherein the dither matrix has each threshold value of the blue noise mask in the dither matrix. Corresponding to each of the threshold regions, the threshold of the blue noise mask is converted into a plurality of threshold data for forming a systematic dot array in the threshold region and arranged, and is the largest in the threshold region. The dither matrix obtained by extracting only the threshold data has a frequency characteristic similar to that of the blue noise mask. Image forming apparatus. 12. The gradation conversion processing means according to claim 9, 10 or 11, wherein the gradation conversion processing means compares the image data with the threshold data and converts the image data into the print data, and each of the threshold regions. Correction value determining means for determining the quantization error generated by the quantization and for determining the correction value for applying the correction to the image data corresponding to the non-quantized threshold area, and the data for accumulating the correction value. An image forming apparatus comprising: a storage unit and a data correction unit that uses the accumulated correction value to correct image data corresponding to a threshold region that has not been quantized. 13. The correction value determining means according to claim 12, wherein the number of threshold values n in the threshold value region and the quantization error of image data corresponding to the threshold value region are E1 to En.
In this case, the sum of E1 to En is set as the quantization error of the threshold region, and the correction value is determined as 1 / n · ΣEn. 14. The threshold data for forming the systematic dot array according to claim 1, wherein dots are regularly arranged in a region by decreasing a brightness value or increasing a density value of the image data. An image forming apparatus characterized in that the threshold value data is a concentration of data. 15. A method of generating a dither matrix using a blue noise mask, wherein each threshold value of the blue noise mask is made to correspond to a threshold region composed of a plurality of threshold value data having a connection relationship, and the threshold value of the blue noise mask is set. Is converted into a plurality of threshold value data for forming a systematic dot array in the threshold area to generate a dither matrix. 16. A copying machine equipped with a scanner, a printer, and a gradation conversion unit for converting image data read by the scanner into print data for printing by the printer, wherein the gradation conversion unit is provided. A copying machine to which the image forming apparatus according to any one of 1 to 13 is applied.